<![CDATA[XYZ is a company engaged in the yarn spinning industry (textile). To achieve the goal, PT. XYZ requires employees with good competence and discipline. Therefore the company assesses employees based on performance values to evaluate employee performance to increase employee productivity. To facilitate data grouping, data mining techniques are needed. This study uses the K-Means algorithm and the Fuzzy C-Means algorithm by grouping the performance data into 4 clusters, namely the level of performance is very good, level of performance is good, level of performance is sufficient and level of performance is less. The results of this study indicate that the Fuzzy C-Means algorithm is a better method than the K-Means algorithm for grouping employee performance data at PT. XYZ because the accuracy value is close to 100%.]]>
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